CONTACT: a non-randomised feasibility study of bluetooth-enabled wearables for contact tracing in UK care homes during the COVID-19 pandemic

Background The need for effective non-pharmaceutical infection prevention measures such as contact tracing in pandemics remains in care homes, but traditional approaches to contact tracing are not feasible in care homes. The CONTACT intervention introduces Bluetooth-enabled wearable devices (BLE wearables) as a potential solution for automated contact tracing. Using structured reports and reports triggered by positive COVID-19 cases in homes, we fed contact patterns and trends back to homes to support better-informed infection prevention decisions and reduce blanket application of restrictive measures. This paper reports on the evaluation of feasibility and acceptability of the intervention prior to a planned definitive cluster randomised trial of the CONTACT BLE wearable intervention. Methods CONTACT was a non-randomised mixed-method feasibility study over 2 months in four English care homes. Recruitment was via care home research networks, with individual consent. Data collection methods included routine data from the devices, case report forms, qualitative interviews (with staff and residents), field observation of care, and an adapted version of the NoMaD survey instrument to explore implementation using Normalisation Process Theory. Quantitative data were analysed using descriptive statistical methods. Qualitative data were thematically analysed using a framework approach and Normalisation Process Theory. Intervention and study delivery were evaluated against predefined progression criteria. Results Of 156 eligible residents, 105 agreed to wear a device, with 102 (97%) starting the intervention. Of 225 eligible staff, 82% (n = 178) participated. Device loss and damage were significant: 11% of resident devices were lost or damaged, ~ 50% were replaced. Staff lost fewer devices, just 6%, but less than 10% were replaced. Fob wearables needed more battery changes than card-type devices (15% vs. 0%). Structured and reactive feedback was variably understood by homes but unlikely to be acted on. Researcher support for interpreting reports was valued. Homes found information useful when it confirmed rather than challenged preconceived contact patterns. Staff privacy concerns were a barrier to adoption. Study procedures added to existing work, making participation burdensome. Study participation benefits did not outweigh perceived burden and were amplified by the pandemic context. CONTACT did not meet its quantitative or qualitative progression criteria. Conclusion CONTACT found a large-scale definitive trial of BLE wearables for contact tracing and feedback-informed IPC in care homes unfeasible and unacceptable — at least in the context of shifting COVID-19 pandemic demands. Future research should co-design interventions and studies with care homes, focusing on successful intervention implementation as well as technical effectiveness. Trial registration ISRCTN registration: 11204126 registered 17/02/2021. Supplementary Information The online version contains supplementary material available at 10.1186/s40814-024-01549-6.


What are the key feasibility ndings?
Despite technical e cacy of the technology, real-world use of BLE wearables in a care home environment and standard procedures associated with cluster randomised trials were not feasible or acceptable to homes -at least not in a pandemic context.
What are the implications of the feasibility ndings for the design of the main study?
The care home context, ampli ed by pandemic conditions and demands, mean any cluster randomised trial of BLE wearables needs to spend su cient time on co-designing a theory and evidence-informed implementation strategy for any intervention as well as robust designs for evaluating effectiveness if it is to be acceptable and feasible to homes.Background COVID-19 disproportionately harmed residents and staff of long-term care homes (nursing and residential homes).In England and Wales, almost 17% of the 274,063 deaths in care homes between March 2020 and February 2022 were COVID-19 related, with the virus implicated in 14% of 9,175 deaths of social care staff. 1 Globally, COVID-19 accounted for 429,265 care home resident deaths between February 2020 and April 2022. 2 The highly transmissible, airborne nature of SARS-CoV-2 in con ned spaces, and widespread frailty amongst residents, rendered care homes particularly vulnerable. 3ccines have not eradicated COVID-19.Non-pharmaceutical infection prevention and control (IPC) measures such as entry regulation (lockdown and quarantine), contact regulation (contact tracing, physical distancing, isolation), transmission reduction measures (screens, masks, surface cleaning), and surveillance (regular testing), will remain important for homes in future waves of COVID-19 4 and for other respiratory infections prevalent and problematic for care homes -notably, in uenza and respiratory syncytial virus (RSV).Homes vary, but IPC measures are often applied on a blanket basis to whole homes, despite needing more high-quality research to validate assumed effectiveness. 4 Contact tracing disrupts infection transmission by identifying and managing individuals exposed to infected people.Its effectiveness hinges on speed, timing, and population tracing comprehensiveness. 5,6In addition to COVID-19, contact tracing can mitigate infections and deaths from communicable diseases like in uenza, norovirus, salmonella, and streptococcus pyogenes, which account for over 50% of care home infections. 7aditional contact tracing involves recalling and stating recent contacts, analysing documentary or observational evidence, or using smartphone Bluetooth or GPS capabilities.Unrealistic methods for care homes as dementia and memory problems impact 70-80% of residents, 8 documentation is sometimes of questionable validity as a record of care delivered, 9 smartphone use by residents is far less than the ~ 60% population coverage required for effective tracing 10 and staff may be discouraged from using phones at work.An alternative approach are systems built around Bluetooth Enabled wearable devices (BLE wearables).BLE wearables harness Bluetooth, low frequency wide area networks/LoRaWAN, and the Internet of Things (IoT) to collect and transmit data on contacts between wearables and IoT devices (who, when, duration, proximity, and location).Wearables can be deployed as fobs, wristwatches, brooches, or cards on lanyards (see Fig. 1).BLE wearables have shown promise for analysing proximity networks in healthcare 11 and modelling infections based on hypothetical adoption. 12Wearables could provide a rapid, automated, and scalable solution for contact tracing in care homes.

The CONTACT intervention
The CONTACT intervention was a BLE wearable and IoT system for collecting data on contacts and feeding back information contact patterns and trends to care homes.BLE wearables and location markers were deployed to pinpoint contact locations.In collaboration with the PROTECT Covid-19 national core study team, we also installed air quality sensors (in two homes) to monitor CO2 levels, temperature, and humidity. 13nsor placement was based on home-supplied oor plans, focusing on areas with high foot tra c, such as communal lounges and dining rooms, and extending to selected bedrooms, staff areas, and key infrastructure (e.g.kitchens).Each system component had a unique QR code identi er allowing us to map each home's system.Each system took two researchers approximately four hours to install.
Consenting staff and residents wore a device while in the home.Each device and location marker's unique identi er enabled secure de-anonymisation for contact and location tracing purposes by the homes.
Contact events (data) from the wearables and location markers were transmitted via a "wave" 14 scanner to a Long-Range Wide Area Network (LoRaWAN) gateway and our commercial partner's (MicroShare®) network.Anonymised data on devices, location marker IDs, and timestamps were sent to our Clinical Trials Research Unit for analysis: summaries of contacts, trends, and infection risks.These provided the basis of feedback to the homes (see Appendices A and B).
Feedback was delivered in a structured monthly report (see appendix A), with ad hoc reports, triggered by noti cation of COVID-19 positive cases (appendix B) detailing contacts between infected residents and other users.Information was presented back to homes at individual and aggregate levels: who had contact with whom, when, where duration of contact, and mean numbers of contacts, aggregate COVID-19 risk, and where most contacts happened.
Reports were based on principles of effective feedback, 15 and co-designed with homes' "study champions": individuals, usually one sometimes two, appointed by homes to take the lead on CONTACT study tasks, advocated for the study and were a point of contact between home and researchers.Evolutionary changes based on staff feedback included adding key messages from the research team and simplifying the visual representation of infection trends.Reports were emailed to the homes.A researcher followed up three days later to address any questions, with interactions documented for our embedded process evaluation.Rationale BLE wearables make contact tracing in homes feasible by collecting and transmitting signi cant contact data, lling an information de cit for homes. 16,17Providing accurate contact information to those in charge of a care home's IPC could lead to better informed, higher-quality, decisions; potentially reducing infections and avoiding blanket application of often restrictive nonpharmaceutical interventions ("lockdowns") regardless of individual infections risk levels.

Research Aims
CONTACT aimed to determine the feasibility and acceptability of a BLE wearable-based contact tracing system among care home residents and staff.
We had three main objectives, informing our decision to proceed to a de nitive cluster randomised controlled trial of CONTACT versus infection prevention and control as usual in homes: i) assess the acceptability and feasibility of intervention delivery processes, by evaluating a. the contact tracing devices and wider system b. the tailored feedback c. intervention delivery and site engagement ii) assess the acceptability and feasibility of study design/implementation processes, by evaluating a. system software b. main study delivery potential c. data collection iii) decide to progress (or not) to main trial by a. evaluating progress against prede ned criteria Methods CONTACT was a non-randomised mixed-methods feasibility study 18 with an embedded parallel process evaluation.It followed a protocol available at https://njl-admin.nihr.ac.uk/document/download/2035361, with ethical approval from the UK Health Research Authority (REC: 294390).A key change from protocol was an initially planned web-based "dashboard" for real-time, continuously updated reports for each home was dropped due to lack of demand from homes.

Participants
Eligibility CONTACT was a whole-home intervention.We included all residents, staff, and visitors willing to wear a device, barring exceptions such as residents with disorders like pica that could pose a risk.Eligible homes needed to assign a champion, promote the study, free staff for training, implement the intervention, provide data, and participate in the process evaluation.

Identi cation and consent
Homes were recruited using care home research networks (National Institute for Health Research ENRICH 19 ; NICHE-Leeds 20 ).
Selection was based on location, sta ng, registration type, and resident characteristics (see Table 1).Whole-home consent was initially planned, but managers' (in two of the homes) perceptions of wider regulatory requirements meant individual consent processes were used.Individual consent was sought from residents, staff, and nominees/consultees for incapacitated residents.

Data collection settings and location
Data were collected in four care homes (Table 1).Home One, in urban West Yorkshire, was a for-pro t residential home run by an employed manager.It had a staff:resident ratio of 1:1, was a converted large house, with experience of previous research studies.
Home Two, a small, owner-managed, for-pro t residential care home in rural West Yorkshire, had a staff:resident ratio of 1.4:1.It was purpose-built and had limited research experience.
Home Three was an owner-managed for-pro t home in a uent North Yorkshire.It was housed in a converted Victorian property, with a staff:resident ratio of 1.6:1.Around 25% of the residents lived with dementia.
Home Four was a family-run, non-private equity owned home with both nursing and residential care provisions.It was in a converted factory with large communal areas.It had a staff:resident ratio of 1.4:1.Three oors catered to residents with differing needs (residential, nursing and dementia).
All homes were rated good by the Care Quality Commission at point of recruitment and demonstrably committed to the study.

Data and analysis
Data were veri ed against a participant list and checked for an appropriate inter-device signal strength.Data not meeting these conditions were excluded.
Physical distance between CONTACT wearables was calculated thus: signi cant contacts at the time of the study. 22 assessed home adherence to study procedures and device management qualitatively, examining study fault logs, weekly support call notes, and process evaluation interviews and observations.This approach accompanied our formal feasibility evaluation against progression criteria.
Home managers completed an adapted version of the NoMaD questionnaire 23 to assess perceptions of factors relevant to embedding CONTACT as an intervention aimed at changing their work practices.NoMaD has good face validity, construct validity and internal consistency. 23antitative data (including time), was collated, cleaned, and described using summary measures of central tendency, variability, missing values, and bias.

OUTCOMES
Table 2 outlines the data collection associated with outcomes and study objectives.Veri cation of data retrieved from MicroShare against list of devices known to be sent to home.For each device to be recording data "correctly" it needed to be issued, not showing a continuous contact of > 6 hours and to have at least one additional contact in a day.Thus, for each device we can compare observed (data) vs. expected (data).
Investigate non-compliance/site adaptations of technology or study processes Reports generated to identify devices that appear inactive which can be used as an indicator of staff non-compliance at site.

Study Objective Data collection method/outcomes
Assess the acceptability and feasibility of intervention delivery processes

Contact Tracing Devices
Site engagement -study delivery Evaluate site willingness and capacity for de nitive main trial; degree of commitment to the study?
Interviews to gain feedback on participation and any potential barriers.
Site issues managing the study?Logs detailing the nature of queries will be recorded.Additional Feedback from interviews with manager/gatekeeper.
Any issues from study team in delivery in the real world?
Interviews with key staff on study procedures.
Feasibility of collecting (planned de nitive study) primary outcome data (COVID-19 test results) Ease of extracting data from care home records; overall number and percentage of residents we know had a COVID-19 test (minimum monthly).The number of positive COVID-19 tests out of those that had a test.

Prespeci ed progression criteria
We evaluated the acceptability and implementation of the CONTACT intervention after two months at study end (see Table 3).

Sample size rationale
In line with feasibility study guidelines, 24 no formal power calculation was undertaken.With more than 30 residents and staff per home, su cient participants were in place.For the qualitative study component, we purposively selected staff based on quali cations (including registered nurses and non-registered care staff), their responsibilities (including team leaders and those in managerial roles), and roles (including care and non-care roles like administration and HR).We interviewed residents from both dementia-focused and non-dementia environments -accepting that many residents in both settings lived with dementia, but that residents living in dementia-focussed environments were more likely to show behaviours that might challenge deployment of the technology.

Recruitment and retention
Between November 2021 and March 2022, the four selected care homes (see Table 1) ran the CONTACT program 24/7 for two months.Despite ending as planned, the feasibility study did not meet its pre-determined progression criteria for a full RCT (Randomized Control Trial).
Of 156 screened residents, 105 consented (either personally or through a nominee) to wear a device, with 102 (97%) wearing them at the start of the two-month intervention.Of the 225 staff deemed eligible, 82.4% (n = 178) agreed to participate, but 20 dropped out before the intervention started.
Ineligibility among residents was solely due to staff concerns that wearing the device could pose a risk of harm.Of the residents who declined to wear the devices, 14 did not give a reason, two were disinterested, four did not receive consent from their nominees, and two passed away before they could return their consent forms.
Of staff, 17 opted not to participate, with eight outright declining, seven not providing a reason, one objecting to wearing the device, and one simply expressing a lack of enthusiasm.Contextual factors for non-participating staff included six leaving the care home, ve with imminent maternity leave, and seven categorized by managers as "rarely present" (sic.)bank staff.
The demographic pro les of the homes were female and white.Most residents had been in the homes for an extended period, and both staff and residents had been vaccinated against COVID-19.More than a third of residents lived with a dementia diagnosis (see Table 4).

Acceptability and feasibility of intervention delivery
Ease of administering devices to residents, staff, and external visitors.
Getting devices to participants was moderately successful, with 69.5% of screened residents and 86.9% of staff receiving BLE wearables.But, participation in CONTACT was burdensome and added to regular.Staff highlighted screening processes, obtaining consent, and registering participants as particularly laborious.COVID-19 restrictions meant homes conducted recruitment themselves.Their limited digital and data infrastructure meant screening was manual and time-consuming.Larger homes bore a heavier burden.Apart from home four however, all homes managed to complete screening on time.
Recruiting residents lacking mental capacity 25 to make decisions for themselves, and thus provide consent, meant contacting designated consultees and further adding to the workload.In some instances, the homes found the workload associated with the study outweighed the perceived bene ts.
"I nd I have to shu e things around to make it work.When things were heavier, I would usually nish at 5, but during the screening and consent time I had to stay late at night to contact the families.It was hard it t it into an already hard day" (Home 1, study champion) The study's research governance requirements contributed to CONTACT's complexity.Every BLE wearable device's unique number (used by the study team) needed to be cross-referenced against a 'master log' in each home for the home to identify the wearer.
Communications involving identi able data were carried out via a secure le transfer system.However, university secure databases for registering participants and reporting Covid-19 cases encountered technical issues, adding further to delays.
Homes 1-3 successfully dispensed devices within a month from consent and before the feasibility start date.Conversely, home four managed to issue only 66% of their BLE wearables after the study start date, with a mean delay of 58.3 days (SD = 26.57).
Because of Home 4, the mean time from consent to issuing resident devices was 41 days (SD = 23.87).Several reasons were given for the 10 resident withdrawals, including residents not wanting to wear a device or feeling distressed or confused by them.
Issuing staff devices was e cient.Homes distributed them within an average of 36 days (SD = 15.31).Home 4 took slightly longer with an average of 41.5 days (SD = 20.32).Reasons for staff withdrawals included no longer wanting to wear the device and nding the device irritating or inconvenient.
An original study objective was assessing the feasibility of BLE wearables for tracking visitors' (relatives and community professionals) movements within the homes.All the homes conveyed that implementing the necessary procedures for this was not possible due to sta ng constraints.Homes one and two did not have permanent reception staff, and the other homes judged the procedures involved too burdensome.Consequently, tracing visitors had to be dropped from study procedures.
We successfully appointed study champions in each home.But it was clear that CONTACT related work was in addition to existing work and so deprioritised: It was the time element.I don't have an administrator or anyone else to help me with my tasks; it's just me.CONTACT wasn't at the top of the list by far.We said we would try our best with it, but we couldn't" (Home 3, manager and champion) Home managers' NoMaD scored aspects of CONTACT familiarity, and current and future chances of "normalisation" (see Table 5).
Managers from Homes 1 and 2 had more familiarity with CONTACT at the end of the study, and the manager of Home 1 believed CONTACT could become a regular part of their operations.Feedback from Homes 2 and 4 was less optimistic (see Table 5).+ No completion point data for Home 1 as home manager left before completion.
Fob wearables required frequent battery changes: 15% (n = 38) in Homes 3 and 4.These were supposed to be done by the homes, but Home 4's delays meant a research team member undertook these over two visits.Card wearables in Homes 1 and 2 required no battery changes.
Acceptability and feasibility of structured CONTACT feedback Home (1, 2 and 4) managers provided assessments of the i) understandability; ii) in uence on IPC thought and iii) likelihood of changes based on the report (Fig. 4).
Figure 4 suggests certain study aspects were challenging and of limited usefulness.Understanding changes in contacts over time, assessing individual risk presentation, and gathering location information were particularly di cult and the least helpful aspects of the intervention.
No home managers were likely to instigate changes based on CONTACT's structured reports.CONTACT's research study context, alongside competing pressures such as maintaining sta ng and pre-existing infection prevention and control (IPC) requirements, reduced the perceived value of the study's information; contributing to an overall perception that the study was of limited value: "The triggered report covered mostly what we knew already.The scheduled report identi ed which residents are most at risk, but what can you really do with that information?We can make people isolate but then you lose staff.The staff do a lateral ow test before work every morning, that's the protection we already have without losing too many staff" (Home 4, study champion) "…it could work, preventing us having to close because we've got 2 cases out of 80 for any infection.We can easily isolate pockets of people if we needed to and staff as well.So, I can see if we didn't have the national guidelines in place, where it would give me research-based information to make risk assessment decisions….In the guidelines, it does say that registered managers are accountable for decisions.Outside of a trial, it would have given me the con dence to say this is what the infection is doing, and we can safely isolate that and carry on doing what we are doing with the other residents, so the residents don't suffer from lack of visitors" (Home 4, manager) A signi cant barrier to feasibility was a staff concern of, "being tracked".A fear that affected trust and compliance with the study.
As a result, scheduled reports were not shared by Home 4's management with other staff.Reports were disseminated in the other homes.The follow-up support call from researchers after each report was perceived as highly bene cial by managers and champions.
Delivering the intervention required training for study champions and home staff.Of the 34 individuals invited to attend virtual training across 9 sessions, almost two-thirds (64.71%) participated.

Data capture
Only around 28.7% (n = 70) of the devices functioned as expected, with only minor differences between resident (29.17%) and staff (28.38%) devices.Differences between (Fig. 5) and within homes (Fig. 6) existed.Apparent device malfunction could be due to battery failure, inappropriate device placement, or staff not updating weekly logs for active devices -a crucial element for correctly processing the dataset.Data transmission from our commercial partner to the university's secure database experienced no issues.
During the feasibility period, 33 (32.35%) of 102 residents and 53 (33.54%) of 158 staff reported COVID-19 infections, suggesting self-reported COVID-19 was a feasible primary outcome.However, the single reported case of staff gastroenteritis suggests, "other infections" was a less feasible outcome.Although all homes provided reported deaths (n = 7, 7.14%) during the intervention, only two homes (3 and 4) shared data regarding whether the deaths were COVID-19 related and the months from registration or device issue to death.Despite 86 infection noti cations, only 52 (60.46%) contact reports were requested by the homes.

Progress against prede ned criteria
The study did not meet any of our quantitative criteria for progression to a de nitive RCT.Additionally, qualitative data from the homes indicated study demands were too burdensome and excessive.Projected compliance and participation rates were too low to justify a de nitive trial.

Criterion Acceptability of the intervention
The number (%) of residents to wearing the device and issued a device at any time during their study period.

62.8%
The number (%) of staff consenting to wearing the device and issued a device at any time during their study period.

67.7%
Provision of the intervention The proportion of issued resident recording "correctly" during the study period.

29.17%
Acceptability of scheduled feedback report Demonstrated acceptability of outputs ascertained through manager interviews

Discussion
A de nitive trial of the CONTACT intervention using BLE wearables and feedback to homes for improved IPC decisions, at least in a pandemic context, was unfeasible.The intervention's development, implementation, and evaluation were executed during the COVID-19 pandemic, a contextual factor that signi cantly reduced the feasibility of the intervention.
The planning and development process was hastily executed, leading to a lack of proper adaptation for a care home context.For instance, BLE fob devices, required cleaning when exposed to human waste or food.More and longer co-produced planning could have allowed for better design adjustments. 26Implementing CONTACT and study procedures was primarily carried out by the care homes, with minimal in-person support from the research team due to pandemic-related restrictions.They did not have the capacity for this implementation work.
We used Normalisation Process Theory (NPT) for planning and implementation to mitigate some of these effects, but its utility was limited in the pressing circumstances of the pandemic. 27The intervention demanded additional work from care homes already struggling with everyday care.CONTACT's perceived bene ts did not su ciently outweigh pre-existing methods of IPC, limiting its appeal. 28The idea of rectifying an information de cit through BLE wearable data and analysis only has merit if information does not come with too high a cost. 29Like other aspects of health and social care, high quality tailored information does not always lead to informed choices. 30The "pull" for the information we were "pushing" 31 was further diminished by thealbeit welcome -development of a successful vaccination programme for COVID-19.
Technical issues were also a barrier.BLE wearables rely on RSSI signal strength to determine proximity and potential exposure.
RSSI can be distorted by physical barriers or other device interference, reducing accuracy. 12,32,33Further, real-world implementation issues led to suboptimal procedure compliance and low population coverage.
As with others' experiences of tech-enabled contact tracing, privacy was a signi cant hurdle to implementation. 34The tracking ability of the technology was seen as intrusive, undermining trust in the technology and IPC amongst staff.CONTACT was designed to offer insight into staff interaction times and movements.This ability to make staff "visible" deterred adoption.
Australian care home research suggest limited interactions may make invisibility more desirable than is sometimes assumed. 35,36til such privacy concerns can be adequately addressed, the widespread use of wearable technology with tracking and tracing capabilities in care homes remains unlikely.
The success of BLE wearables for contact tracing hinges on consistent use and device maintenance by individuals.In care homes, where many residents have cognitive and physical limitations, staff support is crucial.However, staff found the devices intrusive and burdensome.This crucial 28 lack of added value or perceived advantage reduced adoption: unwillingness to encourage residents to participate in the CONTACT study and wear the devices.
CONTACT faced a 12-month delay waiting for the permissions from the UK's Social Care Research Ethics Committee to deliver CONTACT as part of "care as usual" -given the pandemic context.Despite gaining the required permissions, care homes insisted on individual consent procedures, citing fears of punitive action from the Care Quality Commission or litigation risks.These concerns, though unfounded, are indicative of a broader tendency to utilize administrative procedures to mitigate perceived riskseven if such actions might inadvertently compromise care quality. 37They also re ect a wider failure to support care homes' research readiness; despite rhetoric from national research funders to the contrary. 38e movement of people into and between care homes was a signi cant factor in the spread of COVID-19. 39,40The burden associated with the CONTACT study, staff restrictions, and infrastructural de ciencies made it impossible to extend the technology to visitors, thereby missing a key source of potential infection tracing.
Although we provided CONTACT's technology to homes free-of-charge, there were associated costs such as data management, analysis, technical support for system installation, battery changes, and replacement devices.Given the perceived lack of value, it seems unlikely that care homes would be willing to absorb these costs or pass them onto the purchasers of care.
To effectively utilise the information generated by BLE wearables staff need a degree of information literacy to understand concepts like individualized risk and infection trends.Limited numeracy and information skills can be a barrier to innovation in care homes. 41Managers suggested CONTACT's structured reporting used in CONTACT was di cult to comprehend, contributing to the perception that they were unlikely to use the information as a basis for change.This was compounded by a lack of trust in the results among some staff.
Implications for future research CONTACT was unfeasible in a pandemic context.Nonetheless, digital contact tracing systems still have some promise; albeit based on low-quality evidence from modelling and simulation studies. 12,42The implication is that effective implementation is a key determinant of successful contact tracing and improved Infection Prevention and Control (IPC), not the technical e cacy of BLE wearables. 33ture research involving BLE wearable systems should concentrate on applying known strategies for successful research with care homes 26 and dedicating time to co-produce BLE wearable systems that minimize the burden for participating homes.
Facilitators such as privacy, trust, and the utilisation of valuable data from such systems should be a focus of planning and implementation phases.

Distance = 10
^ ((Measured Power-RSSI)/ (10*N)) RSSI (Received Signal Strength Index) was the signal strength as measured by the receiving device.A signal strength of ≤ 75 equated to ≤ 2m.Time was measured in seconds.Contact between devices was in line with government guidance on clinically

Figures
Figures

Figure 5 :
Figure 5: proportion of active devices correctly recording per day by home

Figure 6 :
Figure 6: proportion of active devices correctly recording for residents and staff -Home 2

Table 3 :
CONTACT progression criteria

Table 5
* Rated from 0 (unfamiliar) to 10 (completely familiar) Despite securing the necessary ethical and research governance approvals, we were unable to link residents in the homes to NHS (National Health Service) data.Dialogue with NHS Digital began a year before the intervention period, but linkage proved impossible in the timeframe.DSHC infection and mortality data for the homes was eventually secured -after the intervention period.